The new book, Ask Catalyst: A User’s Guide to TAR, provides detailed answers to 20 basic and advanced questions about TAR, and particularly about advanced TAR 2.0 using continuous active learning.
The questions all came from you – our clients, blog readers and webinar attendees. We receive a lot of good questions about e-discovery technology and specifically about TAR, and we answer every question we get.
Last year, we decided to launch a feature on this blog, Ask Catalyst, to share some of the questions we received and answers we provided. In this book, we’ve collected and arranged the best of them.
The answers are provided by several of the e-discovery experts who work at Catalyst. Authors include Dr. Jeremy Pickens, one of the world’s leading information retrieval scientists; Tom Gricks, the lawyer who was lead e-discovery counsel in the first contested case to win approval for the use of TAR; John Tredennick, the former litigator who founded Catalyst; and yours truly.
The book’s 20 chapters are organized in two parts. Part one focuses on the basics of TAR. Part 2 explores advanced TAR topics.
The Reviews Are In!
We sent advance copies of the book to several noted experts in the field of e-discovery. Here are comments they provided.
From Maura R. Grossman, research professor, University of Waterloo and principal, Maura Grossman Law:
Ask Catalyst: A User’s Guide to TAR fills an important need, providing concrete guidance on how and why continuous active learning (“CAL”) works, and tackling head on the issues that arise in practice when using technology-assisted review for eDiscovery.
From David L. Stanton, leader, Information Law & Electronic Discovery practice, Pillsbury Winthrop Shaw Pittman LLP:
The latest Catalyst publication provides a cogent overview on the effective use of TAR 2.0 in litigation and investigations. It is loaded with practical advice for practitioners at all levels about how this great technology can save time, money and effort. Importantly, the authors show how the continuous learning component of TAR 2.0 avoids controversies over seed sets and stabilization, which often bog down implementations of more basic (TAR 1.0) machine learning technology.
Good information provided by knowledge leaders in the important new field of AI-enhanced document review. Well worth your time to read because many of the basic questions on predictive coding have already been asked and answered.
Catalyst’s Second Book
This is Catalyst’s second book about TAR. Our first book, TAR for Smart People, is an in-depth look at how TAR works and why it matters for legal professionals.